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Pantic I, Paunovic J, Pejic S, Drakulic D, Todorovic A, Stankovic S, Vucevic D, Cumic J, Radosavljevic T. Artificial intelligence approaches to the biochemistry of oxidative stress: Current state of the art. Chem Biol Interact 2022; 358:109888. [PMID: 35296431 DOI: 10.1016/j.cbi.2022.109888] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Revised: 03/04/2022] [Accepted: 03/09/2022] [Indexed: 02/05/2023]
Abstract
Artificial intelligence (AI) and machine learning models are today frequently used for classification and prediction of various biochemical processes and phenomena. In recent years, numerous research efforts have been focused on developing such models for assessment, categorization, and prediction of oxidative stress. Supervised machine learning can successfully automate the process of evaluation and quantification of oxidative damage in biological samples, as well as extract useful data from the abundance of experimental results. In this concise review, we cover the possible applications of neural networks, decision trees and regression analysis as three common strategies in machine learning. We also review recent works on the various weaknesses and limitations of artificial intelligence in biochemistry and related scientific areas. Finally, we discuss future innovative approaches on the ways how AI can contribute to the automation of oxidative stress measurement and diagnosis of diseases associated with oxidative damage.
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Affiliation(s)
- Igor Pantic
- University of Belgrade, Faculty of Medicine, Institute of Medical Physiology, Laboratory for Cellular Physiology, Visegradska 26/II, RS-11129, Belgrade, Serbia; University of Haifa, 199 Abba Hushi Blvd, Mount Carmel, Haifa, IL, 3498838, Israel; Ben-Gurion University of the Negev, Faculty of Health Sciences, Department of Physiology and Cell Biology, 84105 Be'er Sheva, Israel.
| | - Jovana Paunovic
- University of Belgrade, Faculty of Medicine, Institute of Pathological Physiology, Dr Subotica 9, RS-11129, Belgrade, Serbia
| | - Snezana Pejic
- University of Belgrade, Vinca Institute of Nuclear Sciences, Department of Molecular Biology and Endocrinology, Mike Petrovica Alasa 12-14, RS-11351, Belgrade, Serbia
| | - Dunja Drakulic
- University of Belgrade, Vinca Institute of Nuclear Sciences, Department of Molecular Biology and Endocrinology, Mike Petrovica Alasa 12-14, RS-11351, Belgrade, Serbia
| | - Ana Todorovic
- University of Belgrade, Vinca Institute of Nuclear Sciences, Department of Molecular Biology and Endocrinology, Mike Petrovica Alasa 12-14, RS-11351, Belgrade, Serbia
| | - Sanja Stankovic
- University Clinical Centre of Serbia, Centre for Medical Biochemistry, Visegradska 26, RS-11000, Belgrade, Serbia; University of Kragujevac, Faculty of Medical Sciences, Svetozara Markovica 69, RS-34000, Kragujevac, Serbia
| | - Danijela Vucevic
- University of Belgrade, Faculty of Medicine, Institute of Pathological Physiology, Dr Subotica 9, RS-11129, Belgrade, Serbia
| | - Jelena Cumic
- University of Belgrade, Faculty of Medicine, University Clinical Centre of Serbia, Dr. Koste Todorovića 8, RS-11129, Belgrade, Serbia
| | - Tatjana Radosavljevic
- University of Belgrade, Faculty of Medicine, Institute of Pathological Physiology, Dr Subotica 9, RS-11129, Belgrade, Serbia
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Mousavi T, Hadizadeh N, Nikfar S, Abdollahi M. Drug discovery strategies for modulating oxidative stress in gastrointestinal disorders. Expert Opin Drug Discov 2020; 15:1309-1341. [DOI: 10.1080/17460441.2020.1791077] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Affiliation(s)
- Taraneh Mousavi
- Pharmaceutical Sciences Research Center (PSRC), The Institute of Pharmaceutical Sciences (TIPS), Tehran University of Medical Sciences, Tehran, Iran
- School of Pharmacy, Tehran University of Medical Sciences, Tehran, Iran
| | - Nastaran Hadizadeh
- Pharmaceutical Sciences Research Center (PSRC), The Institute of Pharmaceutical Sciences (TIPS), Tehran University of Medical Sciences, Tehran, Iran
- School of Pharmacy, Tehran University of Medical Sciences, Tehran, Iran
- Personalized Medicine Research Center, Endocrinology and Metabolism Research Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Shekoufeh Nikfar
- Pharmaceutical Sciences Research Center (PSRC), The Institute of Pharmaceutical Sciences (TIPS), Tehran University of Medical Sciences, Tehran, Iran
- School of Pharmacy, Tehran University of Medical Sciences, Tehran, Iran
- Personalized Medicine Research Center, Endocrinology and Metabolism Research Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Mohammad Abdollahi
- Pharmaceutical Sciences Research Center (PSRC), The Institute of Pharmaceutical Sciences (TIPS), Tehran University of Medical Sciences, Tehran, Iran
- School of Pharmacy, Tehran University of Medical Sciences, Tehran, Iran
- Personalized Medicine Research Center, Endocrinology and Metabolism Research Institute, Tehran University of Medical Sciences, Tehran, Iran
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